Graduates in tertiary education, in science, math., computing, engineering, manufacturing, construction, by sex - per 1000 of population aged 20-29 ta_eductrain_parteduc_numbgrad__educ_uoe_grad04

Time format:
Years
Unit:
Rate per 1000 population (comparable)
AL
LI
MK
CY
HU
MT
PL
RO
TR
LV
LT
NL
BE
BG
HR
EL
IS
AT
IT
NO
SI
CZ
EU27_2020
LU
RS
SK
DK
EU28
IE
PT
EE
FI
FR
DE
SE
UK
ES
CH
2022
2021
2020
2019
2018
2017
2016
2015
2014
2013
AL
0.3
0.1
LI
0
1.3
0.9
0.5
0
0
0
0
0
MK
0.2
0.1
0.1
0.1
0.1
0.1
0.1
0.1
0.1
0.1
CY
0.3
0.4
0.3
0.3
0.2
0.2
0.3
0.2
0.2
0.2
HU
0.4
0.3
0.2
0.3
0.3
0.2
0.2
0.3
0.3
0.2
MT
0.2
0.1
0.2
0.1
0.1
0.2
0.2
0.2
0.1
0.1
PL
0.3(de)
0.2
0.2
0.3
0.3
0.2
0.3
0.3
0.2
(d)
RO
0.3
0.4
0.2
0.3
0.2
0.2
0.3
0.5
0.5
0.6
TR
0.2
0.2
0.2
0.2
0.2
0.2
0.2
0.1
LV
0.4
0.3
0.2
0.3
0.3
0.3
0.3
0.4
0.4
0.4
LT
0.6
0.4
0.4
0.4
0.4
0.4
0.3
0.4
0.4
0.4
NL
0.4
0.5
0.4
0.5
0.4
0.4
(d)
BE
0.7
0.7
0.6
0.6
0.6
0.5
0.6
0.6
0.5
0.5
BG
0.4
0.4
0.4
0.4
0.4
0.5
0.5
0.5
0.5
0.4
HR
0.7
0.5
0.4
0.4
0.4
0.5
0.4
0.6
0.5
0.5
EL
0.5
0.6
0.5
0.5
0.4
0.5
0.5
0.4
0.4
0.3
IS
0.5
0.7
0.6
0.5
0.3
0.5
0.5
0.5
0.9
0.5
AT
0.6
0.6
0.6
0.6
0.6
0.6
0.6
0.5
0.6
0.6
IT
0.7
0.6
0.6(p)
0.6
0.5
0.6(d)
0.7
0.7
0.7
0.7
NO
0.7
0.6
0.7
0.6
0.6
0.6
0.6
0.6
0.7
SI
0.9
0.6
0.7
0.8
0.7
0.6
3.1
1.5
1.5
1.5
CZ
0.8
0.7
0.6
0.8
0.7
0.7
0.6
0.6
0.6
0.6
EU27_2020
0.7
0.6
0.6
0.6
0.7(d)
0.7
0.7(d)
0.7(d)
0.7(d)
LU
1.3
0.7
0.4
0.6
0.5
0.7
0.4
0.4
0.2
0.3
RS
0.5
0.4
0.5
0.5
0.7
0.7
0.6
0.5
0.3
SK
0.7
0.7
0.6
0.6
0.6
0.7
0.8
0.8
0.9
0.9
DK
0.8
0.8
0.7
0.8
0.8
0.8
0.9
0.9
0.8
0.8
EU28
0.8
0.8(d)
0.8
0.8(d)
0.8(d)
0.7(d)
IE
0.9(d)
0.9(d)
0.9(d)
0.9(d)
0.9(d)
0.8
0.9
0.8
1
0.9
PT
0.7
0.6
0.6
0.7
0.8
0.8
0.9
0.8
0.8
0.9
EE
1
0.8
0.8
0.8
0.8
0.9
0.7
0.6
0.5
0.7
FI
0.8
0.6
0.8
0.8
0.9
0.9
1
1
0.9
0.9
FR
1
0.6
0.6
0.7
0.7(d)
0.9
0.8
0.8
0.8
0.8
DE
0.9
0.9
0.8
0.9
0.9
0.9
0.9
0.9
0.9
0.9
SE
0.9
0.8
0.9
0.8
0.8
0.9
0.9
1
0.9
0.9
UK
1.4
1.3
1.2
1.1
1.1
1.1
1.1
ES
0.8
0.7
0.7
0.7
1.4
1.5
1.3
1.1
0.9
0.8
CH
1.5
1.6
1.5
1.4
1.5
1.3
1.3
1.1
1

Available flags:

b break in time series c confidential
d definition differs, see metadata e estimated
f forecast i see metadata
m imputed n not significant
p provisional r revised
s Eurostat estimate u low reliability
x dropped due to insufficient sample size y unreliable due to small sample size
z not applicable